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Tampering Detection and Localization in Images from Social Networks: A CBIR Approach

  • Cedric Maigrot
  • Ewa Kijak
  • Ronan Sicre
  • Vincent Claveau
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10484)

Abstract

Verifying the authenticity of an image on social networks is crucial to limit the dissemination of false information. In this paper, we propose a system that provides information about tampering localization on such images, in order to help either the user or automatic methods to discriminate truth from falsehood. These images may be subjected to a large number of possible forgeries, which calls for the use of generic methods. Image forensics methods based on local features proved to be effective for the specific case of copy-move forgery. By taking advantage of the number of images available on the internet, we propose a generic system based on image retrieval, followed by image comparison based on local features to localize any kind of tampering in images from social networks. We also propose a large and challenging adapted database of real case images for evaluation.

Keywords

Tampering detection and localization Tweet image analysis Image forgery Copy-move and splicing detection Matching 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Cedric Maigrot
    • 1
  • Ewa Kijak
    • 1
  • Ronan Sicre
    • 2
  • Vincent Claveau
    • 2
  1. 1.Univ. Rennes I, UMR 6074 IRISARennesFrance
  2. 2.CNRS, UMR 6074 IRISARennesFrance

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